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tensor-polinomics
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bert-finetuned-ner

Token Classification
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bert
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  1. README.md +9 -9
  2. model.safetensors +1 -1
  3. runs/Dec15_00-05-28_2050c86a31f4/events.out.tfevents.1765757130.2050c86a31f4.3192.0 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -21,11 +21,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0660
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- - Precision: 0.9417
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- - Recall: 0.9439
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- - F1: 0.9428
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- - Accuracy: 0.9858
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | 0.0818 | 1.0 | 1756 | 0.0657 | 0.9228 | 0.9295 | 0.9261 | 0.9823 |
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- | 0.0383 | 2.0 | 3512 | 0.0678 | 0.9404 | 0.9394 | 0.9399 | 0.9851 |
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- | 0.0247 | 3.0 | 5268 | 0.0660 | 0.9417 | 0.9439 | 0.9428 | 0.9858 |
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  ### Framework versions
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  - Transformers 4.57.3
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  - Pytorch 2.9.1+cu128
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- - Datasets 4.4.1
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  - Tokenizers 0.22.1
 
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  This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0630
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+ - Precision: 0.9419
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+ - Recall: 0.9422
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+ - F1: 0.9421
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+ - Accuracy: 0.9856
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.0794 | 1.0 | 1756 | 0.0672 | 0.9215 | 0.9268 | 0.9241 | 0.9816 |
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+ | 0.038 | 2.0 | 3512 | 0.0719 | 0.9428 | 0.9362 | 0.9395 | 0.9844 |
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+ | 0.0237 | 3.0 | 5268 | 0.0630 | 0.9419 | 0.9422 | 0.9421 | 0.9856 |
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  ### Framework versions
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  - Transformers 4.57.3
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  - Pytorch 2.9.1+cu128
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+ - Datasets 3.6.0
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  - Tokenizers 0.22.1
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